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For the robot-assisted upper limb rehabilitation training process of the elderly with damaged neuromuscular channels and hemiplegic patients, bioelectric signals are added to transform the traditional passive training mode into the active training mode.

This paper mainly builds a steady-state visual stimulation interface, an electroencephalography (EEG) signal processing platform and an exoskeleton robot verification platform. The target flashing stimulation blocks provide visual stimulation at the specified position according to the specified frequency and stimulate EEG signals of different frequency bands. The EEG signal-processing platform constructed in this paper removes the noise by using Butterworth band-pass filtering and common average reference filtering on the obtained signals. Further, the features are extracted to identify the volunteer’s active movement intention through the canonical correlation analysis (CCA) method. The classification results are transmitted to the upper limb exoskeleton robot control system, combined with the position and posture of the exoskeleton robot to control the joint motion of robot.

Through a large number of experimental studies, the average accuracy of offline recognition of motion intention recognition can reach 86.1%. The control strategy with a three-instruction judgment method reduces the average execution error rate of the entire control system to 6.75%. Online experiments verify the feasibility of the steady-state visual evoked potentials (SSVEP)-based rehabilitation system.

An EEG signal analysis method based on SSVEP is integrated into the control of an upper limb exoskeleton robot, transforming the traditional passive training mode into the active training mode. The device used to record EEG is of very low cost, which has the potential to promote the rehabilitation system for further widely applications.

Interaction plays a significant role in robotics and it is considered in all levels of hardware and software control design. Several models have been introduced and developed for controlling robotic interaction. This study aims to address and analyze the state-of-the-art on robotic interaction control by which it is revealed that both practical and theoretical issues have to be faced when designing a controller.

In this review, a critical analysis of the control algorithms developed for robotic interaction tasks is presented. A hierarchical classification of distributed control levels from general aspects to specific control algorithms is also illustrated. Hence, two main control paradigms are discussed together with control approaches and architectures. The challenges of each control approach are discussed and the relevant solutions are presented.

This review presents an evolvement trend of interaction control theories and technologies over time. In addition, it highlights the pros and cons of each control approaches with addressing how the flaws of one control approach were compensated by emerging another control methods.

This review provides the robotic controller designers to select the right architecture and accordingly design the appropriate control algorithm for any given interactive task and with respect to the technology implemented in robotic manipulator.

Currently, rehabilitation medical care is expensive, requires a large number of rehabilitation therapist and which can only limit in the fixed location. In addition, there is a lack of research on the structure optimization and theoretical analysis of soft actuators for hand rehabilitation. In view of the problems above, this paper aims to propose a cheap, portable, wearable soft multiple joints rehabilitation glove.

First, this paper determined the hyperelastic constitutive model by material tensile test. Second, the soft actuator’s internal longitudinal section shape was optimized through the comparison of three diverse chamber structures. Meanwhile, the motion model of the soft actuator is established by the finite element model analysis method. Then, this paper established the constitutive model of the soft actuator according to the torque equilibrium equation and analyzed the relationship between the soft actuator’s bending angle and the input air pressure. This paper has verified that the theoretical model is correct through the soft actuator bending test. Finally, rehabilitation gloves were manufactured according to the model and the rehabilitation performance and grasping ability of gloves were verified through experiments.

The optimization results show that the internal semicircular cavity has better performance. Then, the actuator performance is better after adding the external arc structure and optimizing the physical dimension. The experimental results show that the trajectory of the actuator conforms to the mathematical model and rehabilitation gloves can meet the needs of rehabilitation treatment.

Rehabilitation gloves made of actuators can help patients with hand dysfunction in daily rehabilitation training. Then, it can also assist patients with some fine and complicated hand movements.

This paper proposes a new type of soft rehabilitation glove, which is composed of new soft actuators and adapting pieces. The new actuator is small enough to be fitted to the knuckle of the glove to move each joint of the finger.

The purpose of this paper is to evaluate the physiotherapeutic benefits of bilateral symmetric training (BST) for stroke survivors affected by hemiparesis.

Other studies have investigated symmetric physiotherapy. A key difficulty in previous work is in maintaining mirror-imaged trajectories between the affected and less-affected limbs. This obstacle was overcome in this work by using a two-armed robotic exoskeleton to enforce symmetry. In total, 15 subjects, > 6 months post stroke were, randomly assigned to bilateral symmetric robotic training, unilateral robotic training, and standard physical therapy.

After 12 training sessions (90 minutes/session), the bilateral training group had the greatest intensity of movement training. They also had the greatest improvement in range of motion at the shoulder. The unilateral training group showed the greatest reduction in spasticity.

The rationale for symmetric physiotherapy is that it might promote connections from the undamaged brain hemisphere. The robot generated copious amounts of detailed kinematic data. Even though these data provided insights into the human to machine interface using different training modalities, it proved difficult to draw neurological conclusions. It is recommended that future research along these lines should include measures of neurophysiological change and/or changes in neurological activity.

This research suggests that the advantage of bilateral symmetric movement over other modalities is slight, and that robotic training has comparable results with standard care. If BST is used, care is potentially needed to avoid exacerbation of spasticity. Finally, this research includes a novel quantitative approach for evaluating robotic training.

This study is of value to therapeutic researchers interested in new physiotherapy techniques, roboticists interested in developing rehabilitation devices, or for rehabilitation game designers interested in using virtual reality.

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

Rehab Robotics Ltd and Staffordshire University have been at the leading edge of research and development in the field of rehabilitation robotics for the past 15 years. During this period they have developed the Handy 1 rehabilitation robot which enables people with severe disabilities to gain independence in daily activities such as eating, drinking, shaving, cleaning teeth, washing and applying cosmetics. Handy 1 is widely accepted by experts worldwide as being at the forefront of technology in this area. A consortium of European partners, led by Staffordshire University and sponsored by funding from the European Commission Directorate‐General Information Society Technologies, is about to embark on the development of a new robotic system called Flexibot.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

Assistive technology is a term used to describe any device ranging from simple equipment to complex technologies that can assist a person with a disability. The term is now applied to new technological devices to facilitate active rehabilitation as well as to equipment to enable a person to live with their condition. Current developments such as technology for stroke rehabilitation are rarely brought to the attention of health and social care practitioners, even though frontline staff will be at the forefront of implementation, and their views of the nature of devices and their appropriateness is pivotal. This paper describes some of the technologies being developed to assist the process and delivery of stroke rehabilitation, their potential benefits in practice and stakeholder perceptions of these new technologies.

Human care and service demands will need innovative robotic solutions to make the day‐to‐day life of elderly and disabled people in home and workplace environments easier. The main objective of this work is to develop a new concept of climbing robot for this type of service applications.

ASIBOT is a 5 DOF self‐containing manipulator that includes the entire control system on‐board. The main advantage of this robot is its light weight, about 11 kg with 1.3 m reach. The robot is totally autonomous and only needs a power supply to be operated.

The robot is an arm able to move between different points (Docking stations (DS)) of the rooms and, if necessary, “jump” to (or from) the environment to the wheelchair. In this way the ASIBOT robot could become a home companion and assistance for numerous people.

ASIBOT is a 5 DOF self‐containing light weight manipulator that includes the entire control system on‐board.

The purpose of this paper is to propose a method to avoid hyperstaticity and eventually reduce the magnitude of undesired force/torques. The authors also study the influence of hyperstaticity on human motor control during a redundant task.

Increasing the level of transparency of robotic interfaces is critical to haptic investigations and applications. This issue is particularly important to robotic structures that mimic the human counterpart's morphology and attach directly to the limb. Problems arise for complex joints such as the wrist, which cannot be accurately matched with a traditional mechanical joint. In such cases, mechanical differences between human and robotic joint cause hyperstaticity (i.e. over-constrained) which, coupled with kinematic misalignment, leads to uncontrolled force/torque at the joint. This paper focusses on the prono-supination (PS) degree of freedom of the forearm. The overall force and torque in the wrist PS rotation is quantified by means of a wrist robot.

A practical solution to avoid hyperstaticity and reduce the level of undesired force/torque in the wrist is presented. This technique is shown to reduce 75 percent of the force and 68 percent of the torque. It is also shown an over-constrained mechanism could alter human motor strategies.

The presented solution could be taken into account in the early phase of design of robots. It could also be applied to modify the fixation points of commercial robots in order to reduce the magnitude of reaction forces and avoid changes in motor strategy during the robotic therapy.

In this paper for the first time the authors study the effect of hyperstaticity on both reaction forces and human motor strategies.